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Primary Motor Cortex clinical trials

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NCT ID: NCT05537597 Not yet recruiting - Parkinson's Disease Clinical Trials

Repetitive Transcranial Magnetic Stimulation for Musculoskeletal Pain in Patients With Parkinson's Disease

Start date: January 1, 2023
Phase: N/A
Study type: Interventional

Pain is an increasingly recognized non-motor symptom of Parkinson's disease (PD), with significant prevalence and negative impact on the quality of life of patients. Repetitive transcranial magnetic stimulation (rTMS) of the primary motor cortex(M1)has been proposed to provide definite analgesic effect for pain syndromes. However, very few placebo-controlled studies have been performed specifically to relieve pain in PD. What's more, based on behavioral measures alone, it is impossible to reveal the full network dynamics reflecting the impact of TMS. Electroencephalography (EEG), with high temporal resolution, records signal that its origin in electrical neural activity, which makes it suitable for measuring TMS-evoked activation. By recording the TMS induced neuronal activation directly from the cortex, TMS-EEG provides information on the excitability, effective connectivity of cortical area, thus exploring cortical network properties in different functional brain states. In addition, the use of EEG offers great prospects as a tool to select the right patients in order to achieve adequate, long-term pain relief. Besides assessing the efficacy and safety of high-frequency neuronavigated M1-rTMS in PD patients with musculoskeletal pain, the objective of this study additionally aimed to characterize cortical activation behind pain relief. Influence on motor and other non-motor symptoms after rTMS were also investigated.

NCT ID: NCT04727944 Recruiting - Motor Cortex Clinical Trials

Evaluation of Motor-Related Beta-Activity in Relation to Naturalistic Movement in Healthy Adult Subjects

MOBETA
Start date: July 28, 2022
Phase: N/A
Study type: Interventional

The whole body's voluntary movements are controlled by the brain. One of the brain areas most involved in controlling these voluntary movements is the motor cortex and it is often viewed as the primary 'output' region of the neocortex. Motor cortical activity in the beta frequency range (13-30Hz) is a hallmark signature of healthy and pathological movement, but its behavioral relevance remains unclear. Such uncertainty confounds the development of treatments for diseases of movement which are associated with pathophysiological beta activity, including Parkinson's, therefore furthering understanding on the behavioral significance of activity in this range is now vital. Recently, it has become apparent that oscillatory beta activity actually occurs in discrete transient bursts, and that the summation of short-lasting, high-powered bursts of activity only appear to be sustained oscillations when averaged over multiple trials. In this study we will use neurophysiological and neuroimaging techniques such as electroencephalography (EEG), magnetoencephalography (MEG), and magnetic resonance imaging (MRI). All of these techniques have been identified as non-invasive techniques. By applying these methods, we will be able to analyze beta burst activity in order to determine how beta bursts influence naturalistic motor behavior. This project also encompasses the study of auditory and motor interactions doing an experimental task. The aim of the project is to get a better understanding of the role of motor-related beta activity during the preparation and generation of reach and grasp actions. These findings may inform novel treatments for pathophysiological disorders characterized by aberrant beta signaling, utilizing causal manipulation of the neural circuits implicated in the generation of beta activity. This project also has expected methodological repercussions. It will make it possible to validate the use of individualized head-casts worn during MEG acquisition for the study of the cortical control of naturalistic actions, and to create new analysis tools that allow an increase in the spatial resolution of MEG data.